Lower Bounds for Gas Turbines Aircraft Engines

Mahdi Jemmali, Loai Kayed Bani Melhim, Sayer Obaid B. Alharbi, Abdullah Saeed Bajahzar


Turbine maintenance process is performed periodically at predefined time slots to replace certain turbine parts by new or refurbished parts. The developed heuristics will address the scheduling of turbine maintenance problem to maximize crafts operation time. Scheduling is based on the life span of the replaced parts. Mathematical modeling for the lower bounds of the aircraft turbine maintenance problem will be presented to achieve the desired goal. this study is based on three heuristic categories, the randomized lower bounds, the utilization of the iterative methods solving the subset sum problems and the repeating of the resolution of the knapsack problems.


Heuristic; Scheduling; Randomization algorithms; Parallel Turbines; Gas turbines aircraft engines

Full Text:



B. L. Deuermeyer, D. K. Friesen and M. A. Langston, Scheduling to maximize the minimum processor finish time in a multiprocessor system, SIAM Journal on Algebraic Discrete Methods 3(2) (1982), 190 – 196, DOI: 10.1137/0603019.

D.B. Edmunds, Modular engine maintenance concept considerations for aircraft turbine engines, Aircraft Engineering and Aerospace Technology 50(1) (1978), 14 – 17, DOI: 10.1108/eb035417.

M. Haouari and M. Jemmali, Maximizing the minimum completion time on parallel machines, 4OR 6(4) (2008), 375 – 392, DOI: 10.1007/s10288-007-0053-5.

E. L. Lawler, J. K. Lenstra, A. H. G. R. Kan and D. B.Shmoys, Sequencing and scheduling: algorithms and complexity, Chapter 9, Handbooks in Operations Research and Management Science 4 (1993), 445 – 522, DOI: 10.1016/S0927-0507(05)80189-6.

Z. Tan, Y. He and L. Epstein, Optimal on-line algorithms for the uniform machine scheduling problem with ordinal data, Information and Computation 196(1) (2005), 57 – 70, DOI: 10.1016/j.ic.2004.10.002.

R. Walter, M. Wirth and A. Lawrinenko, Improved approaches to the exact solution of the machine covering problem, Journal of Scheduling 20(2) (2017), 147 – 164, DOI: 10.1007/s10951-016-0477-x.

G. J. Woeginger, A polynomial-time approximation scheme for maximizing the minimum machine completion time, Operations Research Letters 20(4) (1997), 149 – 154, DOI: 10.1016/S0167-6377(96)00055-7.

DOI: http://dx.doi.org/10.26713%2Fcma.v10i3.1218


  • There are currently no refbacks.

eISSN 0975-8607; pISSN 0976-5905